Day-ahead versus intra-day scheduling of microgrids dominated by charging and swapping stations: A Stackelberg game and adaptive rolling forecast optimisation based approach

Abstract

With the rapid development of electric vehicles(EVs), battery charging and swapping stations(BCSSs) have become the carriers of interaction between EVs and smart microgrids(MGs). However, how to effectively utilize the flexibility of BCSSs to meet the charging and battery swapping needs of EVs and manage the balance of energy supply and demand in MGs has not yet been resolved. To this end, this paper proposes a day-ahead bidding and intraday scheduling strategy between charging and swapping station operators(BCSSOs) and microgrid operators (MGOs). Firstly, an evaluation model of the adjustable potential of BCSSs considering the willingness of EV users is established; on this basis, a Stackelberg game model is constructed to realize the day-ahead scheduling of MGO and BCSSO; Secondly, in the intraday stage, the uncertainty of renewable energy output and EV users is solved through an adaptive rolling prediction scheduling model. The example shows that the day-ahead bidding strategy proposed in this paper increases the revenue of MGO by 1.28%, reduces the energy cost of BCSSO by 3.80%, and reduces carbon emissions by 5.78%. Compared with the conventional intraday scheduling method, the adaptive rolling forecast scheduling in this paper can accurately eliminate the deviation caused by uncertainty.